Amyloid-β prediction machine learning model using source-based morphometry across neurocognitive disorders

Abstract Previous studies have developed and explored magnetic resonance imaging (MRI)-based machine learning models for predicting Alzheimer’s disease (AD). However, limited research has focused on models incorporating diverse patient populations. This study aimed to build a clinically useful predi...

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Váldodahkkit:	Yuki Momota, Shogyoku Bun, Jinichi Hirano, Kei Kamiya, Ryo Ueda, Yu Iwabuchi, Keisuke Takahata, Yasuharu Yamamoto, Toshiki Tezuka, Masahito Kubota, Morinobu Seki, Ryo Shikimoto, Yu Mimura, Taishiro Kishimoto, Hajime Tabuchi, Masahiro Jinzaki, Daisuke Ito, Masaru Mimura
Materiálatiipa:	Artigo
Giella:	Inglês
Almmustuhtton:	Nature Portfolio 2024-04-01
Ráidu:	Scientific Reports
Fáttát:	Alzheimer’s disease Amyloid-β Machine learning Magnetic resonance imaging Source-based morphometry
Liŋkkat:	https://doi.org/10.1038/s41598-024-58223-3
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